A time series model of the occurrence of gastric dilatation-volvulus in a population of dogs

<p>Abstract</p> <p>Background</p> <p>Gastric dilatation-volvulus (GDV) is a life-threatening condition of mammals, with increased risk in large breed dogs. The study of its etiological factors is difficult due to the variety of possible living conditions. The associatio...

Full description

Bibliographic Details
Main Authors: Moore George E, Levine Michael
Format: Article
Language:English
Published: BMC 2009-04-01
Series:BMC Veterinary Research
Online Access:http://www.biomedcentral.com/1746-6148/5/12
id doaj-aef533c2076f4f4f83b23603c2015d67
record_format Article
spelling doaj-aef533c2076f4f4f83b23603c2015d672020-11-24T21:23:41ZengBMCBMC Veterinary Research1746-61482009-04-01511210.1186/1746-6148-5-12A time series model of the occurrence of gastric dilatation-volvulus in a population of dogsMoore George ELevine Michael<p>Abstract</p> <p>Background</p> <p>Gastric dilatation-volvulus (GDV) is a life-threatening condition of mammals, with increased risk in large breed dogs. The study of its etiological factors is difficult due to the variety of possible living conditions. The association between meteorological events and the occurrence of GDV has been postulated but remains unclear. This study introduces the binary time series approach to the investigation of the possible meteorological risk factors for GDV. The data collected in a population of high-risk working dogs in Texas was used.</p> <p>Results</p> <p>Minimum and maximum daily atmospheric pressure on the day of GDV event and the maximum daily atmospheric pressure on the day before the GDV event were positively associated with the probability of GDV. All of the odds/multiplicative factors of a day being GDV day were interpreted conditionally on the past GDV occurrences. There was minimal difference between the binary and Poisson general linear models.</p> <p>Conclusion</p> <p>Time series modeling provided a novel method for evaluating the association between meteorological variables and GDV in a large population of dogs. Appropriate application of this method was enhanced by a common environment for the dogs and availability of meteorological data. The potential interaction between weather changes and patient risk factors for GDV deserves further investigation.</p> http://www.biomedcentral.com/1746-6148/5/12
collection DOAJ
language English
format Article
sources DOAJ
author Moore George E
Levine Michael
spellingShingle Moore George E
Levine Michael
A time series model of the occurrence of gastric dilatation-volvulus in a population of dogs
BMC Veterinary Research
author_facet Moore George E
Levine Michael
author_sort Moore George E
title A time series model of the occurrence of gastric dilatation-volvulus in a population of dogs
title_short A time series model of the occurrence of gastric dilatation-volvulus in a population of dogs
title_full A time series model of the occurrence of gastric dilatation-volvulus in a population of dogs
title_fullStr A time series model of the occurrence of gastric dilatation-volvulus in a population of dogs
title_full_unstemmed A time series model of the occurrence of gastric dilatation-volvulus in a population of dogs
title_sort time series model of the occurrence of gastric dilatation-volvulus in a population of dogs
publisher BMC
series BMC Veterinary Research
issn 1746-6148
publishDate 2009-04-01
description <p>Abstract</p> <p>Background</p> <p>Gastric dilatation-volvulus (GDV) is a life-threatening condition of mammals, with increased risk in large breed dogs. The study of its etiological factors is difficult due to the variety of possible living conditions. The association between meteorological events and the occurrence of GDV has been postulated but remains unclear. This study introduces the binary time series approach to the investigation of the possible meteorological risk factors for GDV. The data collected in a population of high-risk working dogs in Texas was used.</p> <p>Results</p> <p>Minimum and maximum daily atmospheric pressure on the day of GDV event and the maximum daily atmospheric pressure on the day before the GDV event were positively associated with the probability of GDV. All of the odds/multiplicative factors of a day being GDV day were interpreted conditionally on the past GDV occurrences. There was minimal difference between the binary and Poisson general linear models.</p> <p>Conclusion</p> <p>Time series modeling provided a novel method for evaluating the association between meteorological variables and GDV in a large population of dogs. Appropriate application of this method was enhanced by a common environment for the dogs and availability of meteorological data. The potential interaction between weather changes and patient risk factors for GDV deserves further investigation.</p>
url http://www.biomedcentral.com/1746-6148/5/12
work_keys_str_mv AT mooregeorgee atimeseriesmodeloftheoccurrenceofgastricdilatationvolvulusinapopulationofdogs
AT levinemichael atimeseriesmodeloftheoccurrenceofgastricdilatationvolvulusinapopulationofdogs
AT mooregeorgee timeseriesmodeloftheoccurrenceofgastricdilatationvolvulusinapopulationofdogs
AT levinemichael timeseriesmodeloftheoccurrenceofgastricdilatationvolvulusinapopulationofdogs
_version_ 1725991682434924544